Download 1a: Overall success rates for bringing novel medicines

Principal Investigator
Dr Mathias Chiano
Applicant Institution
GlaxoSmithKline, Genetics, Gunnels Wood Road, Stevenage, UK
Application Number / Title
20361 - Comprehensive Phenotype-wide Association Studies (PheWAS)for Genetic Tool
Variants relevant to GSK Drug Targets
Keywords
PheWAS, drug-target, genes, association, pathways
Application Lay Summary
1a: Overall success rates for bringing novel medicines to patients are low. Reasons
for failure in drug discovery and clinical development are many and complex,
including choosing wrong target-indication pair(s) and limited understanding of the
biology and mechanisms of action. It is now widely accepted that genetic
associations with disease phenotypes may constitute “drug target validation”
evidence, with improved likelihood of success. This study aims to perform systematic
Phenome-wide association studies (PheWAS) to evaluate associations between
relevant drug-target genes and all health-related outcomes. All genotyping, health
history, biochemistry and linked health-related outcomes will be requested.
1b: This research will systematically evaluate associations between relevant drug
target gene variants and all health-related outcomes. This research will provide
useful results to validate existing target-indication pairs, and discover alternative
indications for existing drugs. Adding human target evidence in portfolio progression
decisions may increase success rates in subsequent clinical development. Focusing
investment in drugs/targets most likely to ultimately deliver patient benefit reduces
patient numbers enrolled in trials that will ultimately fail (wasting patient volunteer
effort and associated risks to patients). This fulfils the UK Biobank’s stated purpose to
improve the prevention, diagnosis and treatment of illnesses.
1c: Variants and combinations of variants in existing and potential drug target genes
will be evaluated for association with all health-related and disease outcomes as well
as markers of disease severity and progression recorded within the UK Biobank.
Initially, analyses will be performed using simple groupings of ICD-10 codes,
followed by more detailed evaluations of disease outcomes and necessary sub-
phenotypes. Genetic association analyses will utilize regression approaches, adjusting
for potential confounders. Results will be submitted for publication in peer reviewed
journals.
1d: We will request data for the full cohort